Convert
converts SQL to ElasticSearch DSL
SQL Features Support:
- SQL Select
- SQL Where
- SQL Order By
- SQL Group By
- SQL AND & OR
- SQL Like & NOT Like
- SQL COUNT distinct count(distinct(mid))
- SQL In & Not In
- SQL Between
- SQL avg(field)、count(*), count(field), min(field), max(field)
Beyond SQL Features Support:
- ES TopHits
- ES date_histogram |||
date_histogram(field="changeTime", _interval="1h", format="yyyy-MM-dd HH:mm:ss")
- ES histogram |||
histogram(field="grade", _interval="10")
- ES STATS |||
stats(field="grade")
- ES RANGE |||
range(field="age", range="20,25,30,35,40")
- ES DATE_RANGE |||
date_range(field="insert_time", format="yyyy-MM-dd" ,range="2014-08-18, 2014-08-17, now-6d,now")
Improvement : now the query DSL is much more flat
SQL Usage
Query
select * from test where a=1 and b="c" and create_time between '2015-01-01T00:00:00+0800' and '2016-01-01T00:00:00+0800' and process_id > 1 order by id desc limit 100,10
Aggregation
select avg(age),min(age),max(age), count(student), count(distinct student) from test group by grade,class limit 10
Beyond SQL
-
range age group 20-25,25-30,30-35,35-40
SELECT COUNT(age) FROM bank GROUP BY range(field="age", range="20,25,30,35,40")
-
range date group by your config
SELECT online FROM online GROUP BY date_range(field="insert_time",format="yyyy-MM-dd" ,range="2014-08-18,2014-08-17,now-8d,now-7d,now-6d,now")
-
range date group by day
select * from test group by date_histogram(field="changeTime", _interval="1h", format="yyyy-MM-dd HH:mm:ss")
-
stats
SELECT online FROM online group by stats(field="grade")
-
topHits
select top_hits(field="class", hitssort="age:desc", taglimit = "10", hitslimit = "1", _source="name,age,class,gender") from school
PKG Usage
github.com/abulo/ratel/elasticsearch/convert
Demo :
package main
import (
"fmt"
"github.com/abulo/ratel/elasticsearch/convert"
)
var sql = `
select * from test where a=1 and b="c" and create_time between '2015-01-01T00:00:00+0800' and '2016-01-01T00:00:00+0800' and process_id > 1 order by id desc limit 100,10
`
var sql2= `
select avg(age),min(age),max(age),count(student) from test group by class limit 10
`
var sql3= `
select * from test group by class,student limit 10
`
var sql4 = `
select * from test group by date_histogram(field="changeTime",interval="1h",format="yyyy-MM-dd HH:mm:ss")
`
func main() {
esql := convert.NewElasticSQL(convert.InitOptions{})
table, dsl, err := esql.SQLConvert(sql)
fmt.Println(table, dsl, err)
}
OUTPUT
date_historgram
{
"query": {
"bool": {
"must": [
{
"match_all": {}
}
]
}
},
"from": 0,
"size": 0,
"aggregations": {
"date_histogram": {
"date_histogram": {
"field": "changeTime",
"format": "yyyy-MM-dd HH:mm:ss",
"interval": "1h"
}
}
}
}
date_range
{
"query": {
"bool": {
"must": [
{
"match_all": {}
}
]
}
},
"from": 0,
"size": 0,
"aggregations": {
"date_range": {
"range": {
"field": "insert_time",
"ranges": [
{
"format": "yyyy-MM-dd",
"from": "2014-08-18",
"to": "2014-08-17"
},
{
"format": "yyyy-MM-dd",
"from": "2014-08-17",
"to": "now-8d"
},
{
"format": "yyyy-MM-dd",
"from": "now-8d",
"to": "now-7d"
},
{
"format": "yyyy-MM-dd",
"from": "now-7d",
"to": "now-6d"
},
{
"format": "yyyy-MM-dd",
"from": "now-6d",
"to": "now"
},
{
"format": "yyyy-MM-dd",
"from": "now"
}
]
}
}
}
}